Chronic <scp>GvHD</scp> in a prognostic model: Graft versus leukemia predictor or immortal time bias?
Authors: Erik G. J. von Asmuth, Arjan C. Lankester, Hein Putter
Journal: American Journal of Hematology (2023)

Zhou et al. recently published a prognostic model for patients with chronic myelomonocytic leukemia (CMML) undergoing allogeneic hematopoietic stem cell transplantation (HSCT) in this journal.1 This score consisted of five items: Age, Blasts, Leukocytes, Anemia, and chronic Graft vs Host Disease (ABLAG). The strongest predictor in this score was the absence of chronic Graft vs Host Disease (cGvHD), with a univariate HR of 3.0, and a multivariate HR of 4.8, with cGvHD occurring in 40% of patients. In this score, all predictors were dichotomized and got a single point, except for the absence of cGvHD, which got two points. Three risk groups were created based on these points: low (0–1), intermediate (2, 3), and high (4+) risk. As the low-risk group consisted of patients with 0 to 1 points, all the patients in the low-risk group must have experienced cGvHD. Patients with cGvHD need to survive at least until cGvHD occurs to be categorized as such. This causes immortal time bias, as survival risk at HSCT is assigned based on events that occur in the future.2 This immortal time is at least 100 days for all patients with cGvHD, as cGvHD can only occur after the first 100 days by definition, but it can be substantially longer for some. We can see this in the survival graphs, with 100% survival for the first 100 days in the low-risk group, both in the derivation and validation cohorts. An even more fundamental problem of incorporating the occurrence of cGvHD in a prognostic model is its applicability: when transplanting a patient with CMML, if a physician wants to use the ABLAG model to evaluate prognosis, they will not know if their patient will get cGvHD and thus cannot apply the model. The concept that cGvHD is associated with a better overall survival in CMML patients has been published before by Itonaga et al.,3 while avoiding immortal bias by using time-dependent covariates and a semi-landmark analysis. This resulted in a lower but significant HR of 2.3. Unfortunately, these techniques cannot be applied to a prognostic model evaluating risk at time of HSCT, since they require knowledge on what happens after HSCT. This lower HR compared with Zhou et al. is in line with mathematical results of Beyersmann et al., which showed immortal time bias will result in an overestimation of the HR in case of no cGvHD.4 Itonaga et al. showed a median time to chronic GvHD of 138 days (range, 100–669 days), showing immortal time would be substantial when not adjusting for it, while Zhou et al. did not publish data on time to cGvHD. Both this and previous studies hypothesize that the presence of cGvHD may improve survival by reducing relapse rate through an increased Graft vs Leukemia effect. However, in this study, overall survival is remarkably similar to non-relapse mortality for all risk groups in the derivation cohort (their figure 1B,C),1 which indicates relapse of disease has a minor impact on overall survival. This indicates that most likely the majority of the prognostic effect of cGvHD on overall survival is not related to a reduced incidence of relapse but attributable to immortal time bias. Still, the other predictors in the model are likely valid, and a remarkable effort has been made to validate the model internally and externally and show superiority over existing models. It would be valuable to refit the model without cGvHD as a covariate and test if model performance still significantly exceeds previous models. Data sharing not applicable to this article as no datasets were generated or analysed during the current study.